The field of image tattooing, which is still called watermarking, is currently booming, and is the subject of much research, both in the fields of video sequences and still images.
We can currently distinguish two main families of image watermarking, respectively corresponding to the watermarking of gray levels images and of color images.
Indeed, the first years of research in the field of watermarking were mainly based on techniques for protecting gray levels images, and led to the use of three distinct fields of marking: the fields of space, frequency and multi-resolution.
The watermarking models in the space field (where the mark is applied directly to the pixel values) have the advantage of only requiring a short calculation time. They are generally resistant to geometrical attacks (for example rotation and changing of scale). The methods proposed are histogram modification (Coltuc D. et al., “Image authentication by exact histogram specification”, workshop on multimedia signal processing, Cannes, France, October 2001) or again patchwork techniques (D. Gruhl, W. Bender, Moritomo, “Techniques for data hiding” in processing SPIE, volume 2420, page 40, February 1995).
As concerns the watermarking models in the frequency field, they have the advantage of being resistant to compression (such as JPEG for example). The mark is applied to the coefficients resulting from a Fourier type transformation (as presented for example by V. Solachidis et I. Pitas, “Self-similar ring shaped watermark embedding in 2-D DFT domain”, 10th European Signal Processing Conference EUSIPCO'2000, Tampere, Finland, pages 1977-1980, September 2000) or Discret Cosinus (as presented for example by F. Alurki and R. Mersereau, “A robust digital watermark procedure for still images using DCT phase modulation”, 10th European Signal Processing Conference EUSIPCO'2000, Tampere, Finland, pages 1961-1964, September 2000).
Marking in the multi-resolution field offers several advantages. It is above all the field used in the most recent compression standards. It also allows the frequency band which will bear the mark to be chosen, thus permitting the risks of the image being damaged by the application of the mark to be reduced (as illustrated by D. Kundur and D. Hatzinakos, “Digital watermarking using multi-resolution wavelet decomposition”, Proceedings of IEEE ICASSP '98, vol. 5, pages 2969-2972, Seattle, Wash., USA, May 1998).
Apart from these watermarking techniques for gray levels images, a second main family of watermarking techniques for still images proposes taking into account the color dimension of the images.
In this family, we can first of all distinguish a first sub-family of techniques consisting of adapting the gray levels methods to the three color components. Parameters are then used to control the force of the marking on each component in order to take into account the characteristics of the human viewing system.
A second sub-family groups methods which are specific to the color images. It takes into account the human viewing system and uses the characteristics of the color representations.
For example, one particular method, specific to color images, is that proposed by L. Akarun, N. Özdilek, B. U. Öztekin, “A Novel Technique for Data Hiding in Color Paletted Images”, Proceedings of the 10th European Signal Processing Conference, EUSIPCO'00, Tampere, Finland, pages 123-126, September 2000.
The first step of this method consists of quantifying the color space using the ‘median-cut’ algorithm. This consists of iteratively partitioning the color space with planes that are perpendicular to the color axes and passing through the median values of the data.
There are two possible cases:                all of the palette is used in the representation of the image, or        certain values of the palette are not used by the image.        
The first case is then no longer adapted to the marking algorithm. However the palette obtained includes colors that the human eye cannot distinguish. By using this property, certain colors of the palette can be liberated, so that they are not used in the image to be marked.
The author proposes that two colors are indiscernible if ΔE<3 where ΔE=√{square root over ((L1−L2)2+(a1−a2)2+(b1−b2)2)}{square root over ((L1−L2)2+(a1−a2)2+(b1−b2)2)}{square root over ((L1−L2)2+(a1−a2)2+(b1−b2)2)} in the Lab space. A reminder is made that the Lab representation space is a perceptually uniform space. L represents the luminance and the a and b components are chromatic.
Let M(i) be the mark, composed of colors that are not part of the palette. The author points out that a binary mark (made up of two colors) is more robust (the risk of detection error is thus reduced).
Let C be the most frequently used color of color histogram, each absciss corresponding to a color of the palette.)
The mark contains a lower number of elements than the number of color pixels C, i<h(C). Each of these elements is indiscernible from the color C.
The marking consists of replacing the ith pixel of color C by M(i).
Another original method is that proposed by S. Battiato, D. Catalano, G. Gallo, R. Gennaro, in “Robust Watermarking for Images based on Color Manipulation”, Proceedings of the 3rd Workshop on Information hiding, LNCS 1768, pages 302-317, Dresden, 1999. According to this method, the mark is not created for the image beforehand, but it is the colorimetric content of the image which represents the mark. One disadvantage of this technique is that it requires a lot of data to be stored.
The color space proposed by the author respects two properties:                the space must be perceptually uniform (as are the Lab and Luv spaces) so that a Euclidian distance measurement can be assimilated to a difference in color for the human viewing system;        the switch to this space, noted LC1C2, must be rapid, simple and have no loss of information.        
The field of opposed colors is defined here from RGB, as follows:
                    RGB        ->                              LC            1                    ⁢                      C            2                    ⁢                      :                                                                    LC            1                    ⁢                      C            2                          ->                  RGB          ⁢                      :                                                  {                                                                                                  L                    =                                          R                      +                      G                      +                      B                                                        ;                                                                                                                                                C                      1                                        =                                                                  2                        ⁢                        B                                            -                      R                      -                      G                                                        ;                                                                                                                          C                    2                                    =                                      R                    -                                          2                      ⁢                      G                                        +                                          b                      .                                                                                                    ⁢                                          ⁢          and                                    {                                                                              R                  =                                                            (                                              L                        +                                                  C                          2                                                -                                                  C                          1                                                                    )                                        /                    3                                                  ;                                                                                        G                =                                                      (                                          L                      -                                              C                        2                                                              )                                    /                  3                                                                                                        B                =                                                      (                                                                  C                        1                                            +                      L                                        )                                    /                  3.                                                                        
According to the authors, this space is the closest to the representation of the chromatic channels of the human viewing system.
The marking is carried out as follows. The mark is a vector M(n), n=1, . . . , k, . . . , N where N is the number of colors of the image and k is a color of the image. Let (LC1C2)k be the color associated to the index k, represented by a vector in the LC1C2 space. A radius is selected in a sphere defined around the coordinate point (LC1C2)k randomly. For each pixel (x,y) corresponding to the color k, the vector corresponding to the (previously determined) radius is added to the initial color vector to obtain the marked vector (LC1C2)k′.
Each color is thus marked by adding a same vector. The marked image is reconstructed by replacing the original colors with the marked colors, by respecting the coordinates of the image pixels.
The mark is then formed by all of the colors of the original image.
Detection is made by comparing the marked image with the marks generated on all of the images processed. This is carried out as follows. Firstly, it must be considered that the image on which the detection is to be made has the same number of colors as the original image. The detection algorithm compares the image to each of the recorded marks. Color by color, a search is made for the closest mark (where the difference vectors between the two pixels of the same coordinate are the most similar). The mark corresponding to the marked image is that with the highest number of difference vectors between the colors of the marked image and the original image in common.
It can be noted that the various publications concerning color watermarking techniques are generally consecrated to the integrity of the visual appearance and the robustness of these techniques against classic attacks is hardly developed.
Generally, for methods whose basic algorithm can be applied to gray levels images, the marking uses the following technique:                switch in the transformed space (wavelet coefficients, discrete cosine coefficients, etc.)        application of the following formula:I′W(i,j)=I′(i,j)+α(i,j)M(i,j)where I′W represents the transform of the marked image (or component), I′ the transform of the original image (or component), M the mark, α the marking intensity control factor, and where i and j represent the coordinates of the processed pixel.        
The algorithms based on the characteristics of the color components are more adapted to the characteristics of the human viewing system. The first article of Kutter M., Jordan F. and Bossen F, (“Digital Signature of Color Images using Amplitude Modulation”, Processing of SPIE storage and retrieval for image and video databases, San Jose, USA, volume 3022, number 5, pages 518-526, February 1997) on color watermarking proposed working on the blue component of the RGB system, for which the human eye is the least sensitive.
This idea was also taken up by A. Reed and B. Hannigan, in “Adaptive Color Watermarking”, Proceedings of SPIE, Electronic Imaging, volume 4675, January 2002. These authors propose working on the yellow component of the system CMY (Cyan Magenta Yellow, which is a colorimetric space), as they considered that the human eye is less sensitive to color variations on the yellow-blue axis.
Generally speaking, the blue component allows the mark to be hidden more effectively (but it is not as strong) and the green component allows the mark to be protected more effectively against attacks (but with greater visual damage to the image). This is explained by the fact that the human viewing system is more sensitive to variations in green than in blue. The compromise between invisibility and strength of the mark therefore depends on the colorimetric nature of the component.
Finally, a last technique, proposed by J. J. Chae, D. Mukherjee, and B. S. Manjunath, in “Color Image Embedding using Multidimensional Lattice Structures”, Proceeding of IEEE International Conference on Image Processing, Chicago, Ill., volume 1, pages 460-464, October 1998, is based on a vectorial type approach.
According to this technique, the first step of the marking consists of breaking down into wavelets the initial image and the signature (which may also be an image). A single breakdown level is used. In this way, the wavelet coefficients of the original image are obtained, noted (CY,CU,CV)(x,y), for which each component corresponds to the color component of the YUV space, and the wavelet coefficients of the mark. The use of the YUV space (space used for video: Y is the luminance component, U and V are chromatic components) thus allows a direct adaptation of this technique to video documents.
The wavelet coefficients resulting from this breakdown of the mark are quantified in β levels. We thus obtain a vector {right arrow over (M)}, (MY,MU,MV)(x,y) for a color mark and M(x,y) for a gray levels, containing (si) elements where 1<i<β.
The integration of the mark can be written as follows:(CY,CU,CV)i′(x,y)=(CY,CU,CV)i(x,y)+α{right arrow over (M)}(si)where α is the control factor for the marking force.
The detection of the mark is then carried out as follows. After application of the transform in wavelets onto the marked image, the resulting coefficients are quantified in β levels.
To estimate the closest vector to that used for the mark, a search is carried out for the quantification value of the closest coefficient to those of the initial image (the mark is then detected, element by element).
The image corresponding to the mark detected can thus be reconstructed by transformation of the inverse wavelets.
All of the gray levels or color watermarking techniques described above have a number of disadvantages.
Therefore, the watermarking techniques for color images based on gray levels algorithms do not permit the color dimension of the images to be taken into account. Consequently, they do not permit the compromise between the invisibility and the strength of the mark to be optimized.
The color image watermarking techniques are very complex and all attempt to satisfy an invisibility objective for the mark. In other words, they are not strong enough to resist classic attacks such as compression or filtering.
The technique proposed by Chae et al. described above, even though it uses a vectorial approach, has the disadvantage of not being resistant to compression. Among others, this marking method does not allow making documents secure to be envisaged. Finally, this technique does not take into account the color dimension of the image, as it attributes the same marking force to the three color components of the image.
Finally, none of the techniques of the prior art using a wavelet breakdown offers blind marking, permitting detection of the mark without the original image being required. Furthermore, none of these techniques offers resistance to JPEG compression, median filtering and the addition of noise.
The particular aim of the invention is to overcome these disadvantages of the prior art.
More precisely, one aim of the invention is to provide a color watermarking technique permitting one or more signatures to be incorporated to a color image.
In other terms, one aim of the invention is to provide a technique for making documents secure by the invisible insertion of a mark.
Another aim of the invention is to implement such a technique that is resistant to most attacks. In particular, one aim of the invention is to provide such a technique which is resistant to compression (especially JPEG type), to filtering (especially by a median filter) and the addition of noise.
The invention has another aim of implementing such a technique which permits blind detection, which is to say that does not require the original image, of the mark in an image.
Another aim of the invention is to provide such a technique permitting the visibility of the mark to be reduced in comparison to the techniques of the prior art.
These aims, as well as others which will become clearer further on, are achieved by a color watermarking process with at least three components.